Most construction worker education and training environments apply traditional teaching methods to educate workers about hazards and productivity in the workplace. Many rely on using conventional ...teacher–student classroom settings, but there are few effective interactive methods applied which can objectively engage trainer and trainees and assess their performance during and after training sessions. Presented is a novel approach towards integrating real-time location tracking and three-dimensional immersive data visualization technologies in existing construction worker education and training environments. The scope is limited to steel-erection tasks performed by union ironworkers in an indoor training center. Results to analysis and visualization of the gathered data from training session are shown. The potential for assessing and improving the trainers' and apprentices' safety and productivity performance is explained. Since such technologies have hardly been used as part of existing construction education and training techniques, the opportunities including return on investment and user feedback were studied. The results show that unsafe practices in worker training environments can be detected and visualized and furthermore their training effectiveness can be indirectly measured.
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•Construction worker education and training can leverage more technology.•Technology is shown that tracks and visualizes the location of workers in real-time.•Algorithms were developed that allow safety and work sampling analysis.•The approach was tested in a worker training center under realistic conditions.•Objective data recording and information visualization are possible.
Despite many safety considerations addressed in lift pre-planning, the ability to provide real-time safety assistance to crane operators and to mitigate human errors during the lifting operation is ...missing. This research developed a framework for real-time pro-active safety assistance for mobile crane lifting operations. First, crane poses are reconstructed in real-time based on the critical motions of crane parts captured by a sensor system. Second, as-is lift site conditions are automatically modeled and updated based on point cloud data. Lastly, the risk of colliding the crane parts and lifted load into nearby obstructions is pro-actively analyzed and warnings are provided to the operator through a graphical user interface. A prototype system was developed based on the framework and deployed on a mobile crane. Field test results indicate that the system can accurately reconstruct crane motion in real-time and provide pro-active warnings that allow the operator to make timely decisions to mitigate the risk.
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•Spatial conflicts and operator errors are major causes in crane related accidents.•A framework for real-time safety assistance for mobile cranes is proposed.•A prototype system has been developed and its implementation described.•Field validation indicates a potential for improving overall crane safety.
Equipment operators play an integral role in the safe and efficient operation of heavy equipment. They observe the environment, understand the situation, and make decisions and actions accordingly. ...Compared with other types of equipment, operating a crane is more sophisticated and mentally demanding, and thus crane operators are more vulnerable to human errors. Therefore, special considerations to mitigate operator errors should be taken when designing an operator-assistance system for construction cranes. With the goal of improving the operators' situation awareness (SA) of safety risks, this research presents a novel framework and practical system architecture for an operator-assistance system by leveraging real-time motion sensing and 3D modeling of dynamic workspaces. An approach for evaluating operators' SA was proposed to validate the effectiveness of the assistance system in actual lifting operations. Results in a series of field tests indicated that the prototype system improved the operators' SA which resulted in an improved lift performance.
•A system architecture for a smart operator-assistance system is introduced.•A query-based measure of situation awareness for crane operators is proposed.•A prototype system was deployed on a real crane for subject SA tests.•Field test results and the effectiveness of a prototype system were analyzed.
•Review of the use of DT for thermal comfort (TC) & energy consumption in buildings.•Technologies were examined in creating DT for TC & energy optimization.•Prediction of energy consumption using ...ANN, AI, deep neural networks, and YOLOv4.•Recommends the use of XR such as AR, VR, and MR for interactive experiences.•Wider adoption of DT to improve user comfort, behavioural action&energy prediction.
In recent years, the integration of digital technologies has grown rapidly in the field of thermal comfort and energy efficiency for buildings. The concept of a digital twin, incorporating multiple digital technologies, has gained increasing attention. The literature lacks a review of the digital twin concept in thermal comfort and energy consumption for existing buildings. This paper conducts a review of the current state-of-the-art in digital twin (DT) technology for thermal comfort/ energy consumption in buildings. The review employs a scientometric approach and examines various technologies used in creating DTs and a systematic analysis of the methods, technologies, algorithms, and approaches used in digital twin experiments. The results show a growing number of studies in this area, with a focus on thermal comfort monitoring, visualization, tracking, energy management, prediction, and optimization for existing buildings. Furthermore, the prediction of energy consumption using algorithms such as Artificial Neural Networks (ANN), Artificial Intelligence (AI), deep neural networks, and YOLOv4 have been used in buildings. However, the wider adoption of a DT that can facilitate occupants, and thermal sensations, enhance human-centered solutions, and improve energy prediction levels are necessary. There is a need for further international collaboration to expand the studies on digital twins for thermal comfort and energy efficiency. The review highlights the limitations and areas of improvement, such as the limited adoption of sensors for environmental measures, the need for more focus on the subjective perception of occupants, and the need for more comparative studies of algorithms for predicting energy consumption. Further studies can be conducted in areas such as understanding occupant psychological responses/behaviors to comfort in the digital world. This will enhance a more consolidated and robust validation for building performance.
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In the Australian construction industry, effective supply chain risk management (SCRM) is critical due to its complex networks and susceptibility to various risks. This study explores the application ...of transformer models like BERT, RoBERTa, DistilBERT, ALBERT, and ELECTRA for Named Entity Recognition (NER) in this context. Utilizing these models, we analyzed news articles to identify and classify entities related to supply chain risks, providing insights into the vulnerabilities within this sector. Among the evaluated models, RoBERTa achieved the highest average F1 score of 0.8580, demonstrating its superior balance in precision and recall for NER in the Australian construction supply chain context. Our findings highlight the potential of NLP-driven solutions to revolutionize SCRM, particularly in geo-specific settings.
Thermal comfort is a complex issue in the built environment due to the physiological and psychological differences of each individual in a building. There is a growing worry over the environmental ...implications of energy use as a result of the warming of the global climate and the growth in the number of instances of extreme weather events. Many review articles have been written, but these reviews have focused on a specific aspect of occupant behavior and thermal comfort. To research the trends of thermal comfort and energy, this research adopted mixed reviews, i.e., quantitative and qualitative, to understand the state-of-the-art factors affecting the thermal comfort of occupants concerning energy, different occupant modeling approaches, functions, and limitations. The in-depth qualitative discussion provides deeper insights into the impacts of occupant behaviors, factors affecting thermal comfort, and occupant behavior modeling approaches. This study classified occupant behaviors into five categories: occupant characteristics, perceptions of the occupant, realistic behaviors, heat gain, and occupant interactions with the system. It also went further to classify the factors affecting the thermal comfort of users based on past works of literature. These include structural, environmental, and human factors. It was concluded that factors that have the most significant impact on energy are human, structural, and environmental factors, respectively. In addition, most of the occupant behavior modeling approaches that have been used in past studies have pros and cons and cannot accurately predict human behaviors because they are stochastic. Future research should be conducted on thermal comfort for different building functions by examining the varied activity intensity levels of users, especially in educational or commercial buildings. Additionally, a proper investigation should be carried out on how thermal insulation of structural members influences thermal comfort. These should be compared in two similar buildings to understand occupant behavioral actions and energy consumption.
This systematic literature review examines the effects of social media use (SMU) and practices (SMPs) on team feedback (TF) and performance (TP) within the context of construction project management. ...It explores the complex interactions between SMU and SMPs and their impact on communication, collaboration, and stakeholder involvement in construction projects. The study investigates how these digital practices transform traditional methods of team interaction, feedback processes, and overall team performance amidst the challenging and diverse backdrop of construction sites. The goal of the review is to offer a detailed insight into the contribution of social media to contemporary construction project management, underscoring its value in boosting team communication, coordination, and effectiveness. This research is pivotal for decoding the changing dynamics of construction management, where digital tools and platforms play a crucial role in achieving project success. The anticipated outcomes are poised to provide significant implications for construction industry professionals, guiding them in harnessing social media for enhanced project management and team cooperation.
Purpose
With the aid of naturalistic simulations, this paper aims to investigate human behavior during manual and autonomous driving modes in complex scenarios.
Design/methodology/approach
The ...simulation environment is established by integrating virtual reality interface with a micro-simulation model. In the simulation, the vehicle autonomy is developed by a framework that integrates artificial neural networks and genetic algorithms. Human-subject experiments are carried, and participants are asked to virtually sit in the developed autonomous vehicle (AV) that allows for both human driving and autopilot functions within a mixed traffic environment.
Findings
Not surprisingly, the inconsistency is identified between two driving modes, in which the AV’s driving maneuver causes the cognitive bias and makes participants feel unsafe. Even though only a shallow portion of the cases that the AV ended up with an accident during the testing stage, participants still frequently intervened during the AV operation. On a similar note, even though the statistical results reflect that the AV drives under perceived high-risk conditions, rarely an actual crash can happen. This suggests that the classic safety surrogate measurement, e.g. time-to-collision, may require adjustment for the mixed traffic flow.
Research limitations/implications
Understanding the behavior of AVs and the behavioral difference between AVs and human drivers are important, where the developed platform is only the first effort to identify the critical scenarios where the AVs might fail to react.
Practical implications
This paper attempts to fill the existing research gap in preparing close-to-reality tools for AV experience and further understanding human behavior during high-level autonomous driving.
Social implications
This work aims to systematically analyze the inconsistency in driving patterns between manual and autopilot modes in various driving scenarios (i.e. multiple scenes and various traffic conditions) to facilitate user acceptance of AV technology.
Originality/value
A close-to-reality tool for AV experience and AV-related behavioral study. A systematic analysis in relation to the inconsistency in driving patterns between manual and autonomous driving. A foundation for identifying the critical scenarios where the AVs might fail to react.
The prevalence of smartphones among vehicle drivers presents exciting opportunities in assessing pavement roughness in a more efficient and cost-effective manner, compared with using conventional ...instruments. This paper describes the body of knowledge in smartphone-based roughness assessment, reports knowledge gaps and casts light on future research directions. First, a systematic literature search found 192 academic publications in relevant fields. These works were critically reviewed with regard to sensor selection, pre-processing methods, and assessment algorithms. Special attention was given to practical factors that are expected to affect the accuracy and robustness of smartphone-based methods, including data collection speed, vehicle type, smartphone specifications and mounting configuration. Findings from this research are expected to provide a thorough understanding of the potentials and limitations of smartphone-based roughness assessment methods and inform future research and practices in this domain.
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•Smartphone-based roughness assessment shows potential to supplement conventional methods.•A systematic performance evaluation of smartphone-based systems is lacking.•Systems that consider both acceleration and vision signals should be explored.•More features from the signal's temporal and spatial domains should be incorporated.
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•A mathematical model is proposed to describe tower crane operation (TCO) hazards.•A hazard estimation method is developed to automatically generate hazard heatmaps.•Integrating ...PSRRT* and BIM enables safety analyses at various spatial–temporal granularity.•Situation awareness of the schedule, planning, and execution of on-site activities is improved.
As an increasing number of building components are modularized and prefabricated, tower cranes are required to lift larger and heavier loads. This situation increased the risk of crane failure and the severity of crane accidents, challenging the effectiveness of conventional reactive safety management approaches. Thus, early hazard recognition and proactive control (Prevention through Design, PtD) are necessitated to manage Tower Crane Operation (TCO) hazards. This study proposes an automatic PtD method to manage the Hazard Exposure (HE) brought by one or multiple tower crane operations on construction sites in the construction planning stage by leveraging a path-finding algorithm and Building Information Modelling (BIM)-enabled spatial–temporal analyses. The dynamic distribution of TCO hazards is estimated based on safe and practical lift paths generated by a path-finding algorithm, and visualized as HE heatmaps in BIM models. Three application scenarios of the HE estimation and visualization are explored, including managing critical lifts, improving daily hazard communication on site, and contextualizing scheduling/planning tasks with hazard information. Estimating and visualizing HE in these scenarios are expected to allow planners and safety managers arrange activities and workspaces to minimize the risks of TCO hazards. The contributions of the paper include (1) proposing a generic energy-based quantification model for different types of TCO hazards, (2) increasing the spatial–temporal granularity of the HE estimation and visualization, and (3) promoting proactive controlling measures over the TCO hazards through planning, scheduling, and the coordination of crane operations with other on-site activities.
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